Data from: Digital twin mathematical models suggest individualized hemorrhagic shock resuscitation strategies

Background: Optimizing resuscitation to reduce inflammation and organ
dysfunction following human trauma-associated hemorrhagic shock is a major
clinical hurdle. This is limited by the short duration of pre-clinical
studies and the sparsity of early data in the clinical setting. Methods:
We sought to bridge this gap by linking preclinical data in the porcine
model with clinical data from patients from the Prospective,
Observational, Multicenter, Major Trauma Transfusion (PROMMTT) study via a
three-compartment ordinary differential equation model of inflammation and
coagulation. Results: The model accurately predicts physiologic,
inflammatory, and laboratory measures in both the porcine model and
patients, as well as the outcome and time of death in the PROMMTT cohort.
Model simulation suggests that resuscitation with plasma and red blood
cells outperformed resuscitation with crystalloid or plasma alone, and
that earlier plasma resuscitation reduced injury severity and increased
survival time. Conclusions: This workflow may serve as a translational
bridge from pre-clinical to clinical studies in trauma-associated
hemorrhagic shock and other complex disease settings.

背景：优化复苏策略以减轻人类创伤相关性失血性休克后的炎症反应及器官功能障碍，是一项重大临床难题。这一领域的研究进展受限于临床前研究持续时间较短，以及临床场景下早期数据的稀缺性。

方法：我们通过建立炎症与凝血的三房室常微分方程模型，将猪模型的临床前数据与前瞻性、观察性、多中心、重大创伤输血（PROMMTT）研究中的患者临床数据关联起来，旨在填补这一空白。

结果：该模型可准确预测猪模型与患者的生理、炎症及实验室指标，同时能预测PROMMTT队列中的患者结局与死亡时间。模型模拟结果显示，采用血浆联合红细胞的复苏方案优于单纯晶体液或单纯血浆复苏，且早期血浆复苏可降低损伤严重程度并延长生存时间。

结论：该工作流程有望成为创伤相关性失血性休克及其他复杂疾病领域中，连接临床前研究与临床研究的转化桥梁。